Data Imputation Model for Internet of Medical Things (IoMT) Using Nonlinear Autoregressive Exogenous (NARX) network Model

Autor:	DHAMODHARAVADHANI S, Rathipriya R
Rok vydání:	2022
DOI:	10.21203/rs.3.rs-1903849/v1
Popis:	The objective of this paper is to propose a data transmission reduction approach using Nonlinear Autoregressive Exogenous (NARX) network based prediction model to minimise energy consumption in sensor nodes (SNs) and base stations (BS). The NARX based prediction model is used to impute the missing sensor values by the base station. The imputation of missing transmitted sensor data is compensated by the base station using historical sensor data and sensor values of the interrelated sensor data in Internet of Medical Things (IoMT). The purpose of this paper is to achieve energy conservation by reducing the amount of redundant sensor data transmitted over the IoMT when data is not received at Time stamp‘t’.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::014b6a9cf0a043b34c18d024be803d95 https://doi.org/10.21203/rs.3.rs-1903849/v1 Zobrazit plný text záznamu